Pain remains a significant public health issue with two-thirds of patients achieving little to no pain relief from the myriad of currently available pharmacotherapies and dosing regimens. The use of opioid (e.g. morphine) pharmacotherapies produces several rewarding and reinforcing side effects, which result in the drugs’ diversion to abuse settings. Glial cells have been found to play a critical role in initiating and maintaining increased nociception in response to peripheral nerve injury. The opioids-induced glial cell activation attenuates opioid-induced pain suppression and enhances the development of opioid tolerance and dependence, the drug reward, and other negative side effects such as respiratory depression. We are interested in employing structure-based drug design and high-throughput screening techniques to identify novel small-molecule inhibitors of the cell surface receptors that regulate glial cell activation. The identified agents will potentially serve as therapeutics that suppresses opioid-dependence and tolerance.

Fig (Left) Potentiation of opioid analgesics by targeting the TLR4-mediated glial activation. (A) Opioids activate glia by triggering the signal transduction mediated by the TLR4 (dimeric form in complex with MD-2), resulting in the release of cytokine intercellular mediator, interleukin-1 (IL-1), and suppressing the desired opioid-induced neuronal analgesia effect. (B) In the presence of the antagonists of the TLR4-signaling, such as inhibitors of the critical TLR4 homodimerization or the TLR4/MD-2 interactions, glia stay in the resting state. Opioids (red star) cause analgesia by binding to opioid receptors (orange hexagon). (Right) Designs of peptide antagonists of the TLR4/MD-2 binding based on the TLR4-binding region of MD-2.

The work is being done with The YIN Lab Research (UC@Boulder)

Solvation energy contribution to protein-ligand binding conceptually consists of two different contributions. The first one is collective in nature, comes from the long range interaction of the molecules charges with polar water molecules. The other comes mostly from the short range interactions of the molecules in question with the adjacent layer of the water molecules.

The long range part can be, to a certain extent, be modeled within a continuous electrostatics framework. Recently we have posted a number of improvements to commonly used Generalized Born models. Let us show that GB models may naturally have a good built-in approximation for the surface accessible area for the non-polar contribution calculations.

To do that we take  FSBE model as the example and suggest the following equation for the surface area of a molecule:



where is a coefficient, are the surface tensions associated with the atom types, are the radii of the ions and are the Born radii defined according to the model settings, e.g.



The results of the model surface area differences for 230 protein ligand complexes (the model vs. exact surface data) are presented on the graph. The numbers show an impressive correlation with .

The surface area requires the same power of the Born radii for the evaluation and thus can be implemented both numerically accurate and computationally efficient.